Feminism With Analysis Of Women Characters English Literature Essay

Feminism With Analysis Of Women Characters English Literature Essay Virginia Woolf was born in 1882, the youngest daughter of the large and talented Stephen family. Her father Leslie Stephen was a critic, biographer, and philosopher. Her mother, Julia Stephen, was a daughter of the novelist William Makepeace Thacker. So, Virginia Woolf was destined to be a writer. Although at these times only the boys were allowed to have the formal education, she was lucky to take advantage from her fathers rich library. Besides, Virginia Woolf was a manic-depressive; primary cause is that she couldnt tolerate the absurdity of life and she was under the influence of the psychological stress caused by war. She feared that her madness would return and she would not be able to continue writing. Woolf committed suicide by drowning herself in a river in March 1941. Virginia Woolf is a pioneer of feminism. Since her death, she is acknowledged as one of the major novelists of the 20th century, and best known for her  stream of consciousness  method, which gives readers the impression of being inside the mind of the character and an internal view, that she had used in her novel Mrs. Dalloway. Mrs. Dalloway originally published in 1925, is a novel containing the themes; war, death, communication and especially feminism -the pressure on women and the roles of women of the time period-. It is clear that Virginia Woolf was aware of the problems and loss of the modern life and Mrs. Dalloway criticizes the patriarchal culture. Actually 1920s brought new and exciting cultural innovations that shifted womens attention from politics into social life. Shannon Forbes mention this in her article as; The concept of performance is key to understanding the way gender for Woolf is a social construct stemming for women from their struggle to identify and simultaneously oppose the Victorian ideology forcing them to equate their identity with a corresponding and acceptable Victorian role(Forbes, 50). She portrayed different types of women in various contexts. She opened womens eyes on their inferior status and provided them with a female tradition to rely on. The novel is very successful sh owing the intellectual commitment to political, social and feminist principles. The story takes place in just one day of the life of Clarissa Dalloway, who is thinking about her true feelings, her past life, her decisions, the pressure that the society enforces on her and the women roles while planning a party for the evening. The feminist tone is established from the very beginning of the novel. On this day Peter Walsh, the most important love-story of Clarissas life, comes unexpectedly. Clarissa cannot prevent herself from thinking about Peter and the old days before her marriage. They used to love each others but their relationship ended with a failure. Peter was always trying to dominate and have a total control in Clarissas life, however Clarissa want a little freedom in their relationship, she believes that the privacy is an indispensable element in a relationship and without it psychologically she could not afford a marriage. Thats why she rejected Peters marriage proposal. She gives reasons for rejecting him and marrying Richard like; For in marriage a little license, a little independence there must be between people living together day in day out in the same house; which Richard gave her, and she him (where was he this morning, for instance? Some committee, she never asked what.) But with Peter e verything had to be shared, everything gone into (7). Clarissa rejected Peter because his love was too possessive and domineering. Furthermore, Peter could not provide the gentleness and the love that Clarissa need and deserve. Dialogues between herself and Peter in Clarissas memories, shows that although he loved her, he did not conceal his feelings, but he would humor her; It was the state of the world that interested him; Wagner, Popes poetry, peoples characters eternally, and the defects of her own soul. How he scolded her! How they argued! She would marry a Prime Minister and stand at the top of a staircase; the perfect hostess he called her (she had cried over it in her bedroom), she had the makings of the perfect hostess, he said(7). Although Clarissa is portrayed as a suppressed women character who has no intellectual interest but knows very well how to succeed in social relationships and how to welcome guests, the big decision about not to marrying Peter who did not give he r independence and sufficient love, strongly indicates that she is a powerful and quite intelligent women. Hereby Clarissa may seem by society like a classical women of the 1920s, perfect wife and mother who welcome guests in her lovely house, supports her happy family, pleases her husband, but once in the novel enters her mind with the stream of consciousness  method and made the reader learn her true feelings and thoughts, it is understood that she is much more than a house wife, she has her own feelings, ideologies and beliefs. Later on, Sally Seton who is an old friend -and lover- of Clarissa, exists mostly just as figure in her memory in the novel, appears at Clarissas party. She is a modern woman who does not care about the customs, traditions and classic social role of women. Throughout the novel it is stated that she smokes, runs naked in the corridors of cottages, and travels by boat in midnights in other words lives in the way that she wants. She is also against the bourgeoisie and the noble class further she always depends freedom for women; so she has her own political views and ideologies that she does not fear to express. She is an anti-patriarchal woman. She asserted herself as a woman and demanded equal rights for women. Sally was Clarissas inspiration to push her to think beyond the walls of Bourton, read and philosophize. There they sat, hour after hour, talking about life, how they were to reform the world. They meant to found a society to abolish private property(33). Ä °n the novel, Sally Seaton is the symbol of the feminism ideology. She defends the women rights and rejects the patriarchal culture. There are indications in the novel that some women were beginning to take on roles of power in those days. For instance, Lady Bruton was a lady in a position of power.   She is a sixty-two years old woman, who is famous with the passion for politics. She speaks like a man, acts with tough attitudes. She is also represented as a selfish, noble, strong, brave and proud woman. Lady Brutons strong independence as a leader shows the movement towards tolerance of women being in power. With the characterization of Lady Bruton, it is denoted that being strong and independent as a women is not impossible and is not a crime. In Mrs. Dalloway, the dark picture of patriarchal society is portrayed through Septimus Rezia relationship. The sense of a wifes duty is also demonstrated in the character Rezia wife of Septimus Smith the mentally disturbed soldier  returned from the war. Rezia, although she loves her husband very much, and cannot imagine living without him, feels the burden of having to care for her ill husband. The terrible influence of patriarchy is effectively portrayed through the presentation of Rezias lives. She is a victim of the cruelty of the social and political doctrine of the English society and their only guilt is that they are merely women. What is really tragic about Rezia is not her husbands death, but the unfriendly manner in which the world treats her. Once again, Woolf describes the inequalities of life and the pressures that society puts on women. Another example of the unconventional woman is portrayed through the character of Elizabeth Dalloway, the daughter of the Dalloway family. In the novel she is descripted as a very beautiful girl and many boys in London like her. But Elizabeth  is extremely  angry with the mens attitude toward her. She prefers to be recognized with her intelligence rather than her beauty. Unlike her mother, she does not care about the tea parties, dinners and meetings. With a sudden impulse, with a violent anguish, for this woman was taking her daughter from her, Clarissa leant over the banisters and cried out, Remember the party! Remember our party to- night. But Elizabeth had already opened the front door; there was a van passing; she didnt answer(130). Elizabeth has ambitions to have a career and a professional life. She has planned to be a doctor, farmer, or to go into Parliament. She is important in the novel since she is like the delegate of the new generations feminism and she represents th e future life that women and men have equal places in the society. Ä °n conclusion, there are many female characters in the book. Some of them seem like weak woman and some are strong in a male dominated society. However with the deep examinations of all of them, it is explicated that they all have strong feelings and ideas. Every human is a mixture of his/her concepts, memories, emotions; still, that same human being leaves behind as many different impressions as there are people who associate with that person. Furthermore, Woolf evokes in her journals the following question: If everyones impression of another is just a fragment of the whole, what is the real world like?(57)

Regression Analysis

REGRESSION ANALYSIS Correlation only indicates the degree and direction of relationship between two variables. It does not, necessarily connote a cause-effect relationship. Even when there are grounds to believe the causal relationship exits, correlation does not tell us which variable is the cause and which, the effect. For example, the demand for a commodity and its price will generally be found to be correlated, but the question whether demand depends on price or vice-versa; will not be answered by correlation. The dictionary meaning of the ‘regression’ is the act of the returning or going back. The term ‘regression’ was first used by Francis Galton in 1877 while studying the relationship between the heights of fathers and sons. â€Å"Regression is the measure of the average relationship between two or more variables in terms of the original units of data. † The line of regression is the line, which gives the best estimate to the values of one variable for any specific values of other variables. For two variables on regression analysis, there are two regression lines. One line as the regression of x on y and other is for regression of y on x. These two regression line show the average relationship between the two variables. The regression line of y on x gives the most probable value of y for given value of x and the regression line of x and y gives the most probable values of x for the given value of y. For perfect correlation, positive or negative i. e. for r=  ±, the two lines coincide i. e. we will find only one straight line. If r=0, i. e. both the variance are independent then the two lines will cut each other at a right angle. In this case the two lines will be  ¦to x and y axis. The Graph is given below:- We restrict our discussion to linear relationships only that is the equations to be considered are 1- y=a+bx – x=a+by In equation first x is called the independent variable and y the dependent variable. Conditional on the x value, the equations gives the variation of y. In other words ,it means that corresponding to each value of x ,there is whole conditional probability distribution of y. Similar discussion holds for the equation second, where y acts as independent variable and x as dependent variable. What purpose does regression line serve? 1- The first object is to estimate the dependent variable from known values of independent variable. This is possible from regression line. – The next objective is to obtain a measure of the error involved in using regression line for estimation. 3- With the help of regression coefficients we can calculate the correlation coefficient. The square of correlation coefficient (r), is called coefficient of determination, measure the degree of association of correlation that exits between two variables. What is the difference between correlation and linear regression? Correlation and linear regression are not the same. Consider these differences: †¢ Correlation quantifies the degree to which two variables are related. Correlation does not find  a best-fit line (that is regression). You simply are computing a correlation coefficient (r) that tells you how much one variable tends to change when the other one does. †¢ With correlation you don't have to think about cause and effect. You simply quantify how well two variables relate to each other. With regression, you do have to think about cause and effect as the regression line is determined as the best way to predict Y from X. †¢ With correlation,  it doesn't matter which of the two variables you call â€Å"X† and which you call â€Å"Y†. You'll get the same correlation coefficient if you swap the two. With linear regression, the decision of which variable you call â€Å"X† and which you call â€Å"Y† matters a lot, as you'll get a different best-fit line if you swap the two. The line that best predicts Y from X is not the same as the line that predicts X from Y. †¢ Correlation is almost always used when you measure both variables. It rarely is appropriate when one variable is something you experimentally manipulate. With linear regression, the X variable is often something you experimental manipulate (time, concentration†¦ and the Y variable is something you measure. Regression analysis is widely used for  prediction  (including  forecasting  of  time-series  data). Use of regression analysis for prediction has substantial overlap with the field of  machine learning. Regression analysis is also used to understand which among the independent variables are related to the dependent variable, and to explore the forms of these relationships. In restricted circumstances, regression analysis can be used to infer  causal relationships  between the independent and dependent variables. A large body of techniques for carrying out regression analysis has been developed. Familiar methods such as  linear regression  and  ordinary least squares  regression are  parametric, in that the regression function is defined in terms of a finite number of unknown  parameters  that are estimated from the  data. Nonparametric regression  refers to techniques that allow the regression function to lie in a specified set of  functions, which may beinfinite-dimensional. The performance of regression analysis methods in practice depends on the form of the data-generating process, and how it relates to the regression approach being used. Since the true form of the data-generating process is not known, regression analysis depends to some extent on making assumptions about this process. These assumptions are sometimes (but not always) testable if a large amount of data is available. Regression models for prediction are often useful even when the assumptions are moderately violated, although they may not perform optimally. However when carrying out  inference  using regression models, especially involving small  effects  or questions of  causality  based on  observational data, regression methods must be used cautiously as they can easily give misleading results. Underlying assumptions Classical assumptions for regression analysis include: ? The sample must be representative of the population for the inference prediction. ? The error is assumed to be a  random variable  with a mean of zero conditional on the explanatory variables. ? The variables are error-free. If this is not so, modeling may be done using  errors-in-variables model  techniques. ? The predictors must be  linearly independent, i. e. it must not be possible to express any predictor as a linear combination of the others. SeeMulticollinearity. The errors are  uncorrelated, that is, the  variance-covariance matrix  of the errors is  diagonal  and each non-zero element is the variance of the error. ? The variance of the error is constant across observations (homoscedasticity). If not,  weighted least squares  or other methods might be used. These are sufficient (but not all necessary) conditions for the least-squares estimator to possess desirable propertie s, in particular, these assumptions imply that the parameter estimates will be  unbiased,  consistent, and  efficient  in the class of linear unbiased estimators. Many of these assumptions may be relaxed in more advanced treatments. Basic Formula of Regression Analysis:- X=a+by (Regression line x on y) Y=a+bx (Regression line y on x) 1st – Regression equation of x on y:- 2nd – Regression equation of y on x:- Regression Coefficient:- Case 1st – when x on y means regression coefficient is ‘bxy’ Case 2nd – when y on x means regression coefficient is ‘byx’ Least Square Estimation:- The main object of constructing statistical relationship is to predict or explain the effects on one dependent variable resulting from changes in one or more explanatory variables. Under the least square criteria, the line of best fit is said to be that which minimizes the sum of the squared residuals between the points of the graph and the points of straight line. The least squares method is the most widely used procedure for developing estimates of the model parameters. The graph of the estimated regression equation for simple linear regression is a straight line approximation to the relationship between y and x. When regression equations obtained directly that is without taking deviation from actual or assumed mean then the two Normal equations are to be solved simultaneously as follows; For Regression Equation of x on y i. e. x=a+by The two Normal Equations are:- For Regression Equation of y on x i. e. y=a+bx The two Normal Equations are:- Remarks:- 1- It may be noted that both the regression coefficient ( x on y means bxy and y on x means byx ) cannot exceed 1. 2- Both the regression coefficient shall either be positive + or negative -. 3- Correlation coefficient (r) will have same sign as that of regression coefficient. Regression Analysis REGRESSION ANALYSIS Correlation only indicates the degree and direction of relationship between two variables. It does not, necessarily connote a cause-effect relationship. Even when there are grounds to believe the causal relationship exits, correlation does not tell us which variable is the cause and which, the effect. For example, the demand for a commodity and its price will generally be found to be correlated, but the question whether demand depends on price or vice-versa; will not be answered by correlation. The dictionary meaning of the ‘regression’ is the act of the returning or going back. The term ‘regression’ was first used by Francis Galton in 1877 while studying the relationship between the heights of fathers and sons. â€Å"Regression is the measure of the average relationship between two or more variables in terms of the original units of data. † The line of regression is the line, which gives the best estimate to the values of one variable for any specific values of other variables. For two variables on regression analysis, there are two regression lines. One line as the regression of x on y and other is for regression of y on x. These two regression line show the average relationship between the two variables. The regression line of y on x gives the most probable value of y for given value of x and the regression line of x and y gives the most probable values of x for the given value of y. For perfect correlation, positive or negative i. e. for r=  ±, the two lines coincide i. e. we will find only one straight line. If r=0, i. e. both the variance are independent then the two lines will cut each other at a right angle. In this case the two lines will be  ¦to x and y axis. The Graph is given below:- We restrict our discussion to linear relationships only that is the equations to be considered are 1- y=a+bx – x=a+by In equation first x is called the independent variable and y the dependent variable. Conditional on the x value, the equations gives the variation of y. In other words ,it means that corresponding to each value of x ,there is whole conditional probability distribution of y. Similar discussion holds for the equation second, where y acts as independent variable and x as dependent variable. What purpose does regression line serve? 1- The first object is to estimate the dependent variable from known values of independent variable. This is possible from regression line. – The next objective is to obtain a measure of the error involved in using regression line for estimation. 3- With the help of regression coefficients we can calculate the correlation coefficient. The square of correlation coefficient (r), is called coefficient of determination, measure the degree of association of correlation that exits between two variables. What is the difference between correlation and linear regression? Correlation and linear regression are not the same. Consider these differences: †¢ Correlation quantifies the degree to which two variables are related. Correlation does not find  a best-fit line (that is regression). You simply are computing a correlation coefficient (r) that tells you how much one variable tends to change when the other one does. †¢ With correlation you don't have to think about cause and effect. You simply quantify how well two variables relate to each other. With regression, you do have to think about cause and effect as the regression line is determined as the best way to predict Y from X. †¢ With correlation,  it doesn't matter which of the two variables you call â€Å"X† and which you call â€Å"Y†. You'll get the same correlation coefficient if you swap the two. With linear regression, the decision of which variable you call â€Å"X† and which you call â€Å"Y† matters a lot, as you'll get a different best-fit line if you swap the two. The line that best predicts Y from X is not the same as the line that predicts X from Y. †¢ Correlation is almost always used when you measure both variables. It rarely is appropriate when one variable is something you experimentally manipulate. With linear regression, the X variable is often something you experimental manipulate (time, concentration†¦ and the Y variable is something you measure. Regression analysis is widely used for  prediction  (including  forecasting  of  time-series  data). Use of regression analysis for prediction has substantial overlap with the field of  machine learning. Regression analysis is also used to understand which among the independent variables are related to the dependent variable, and to explore the forms of these relationships. In restricted circumstances, regression analysis can be used to infer  causal relationships  between the independent and dependent variables. A large body of techniques for carrying out regression analysis has been developed. Familiar methods such as  linear regression  and  ordinary least squares  regression are  parametric, in that the regression function is defined in terms of a finite number of unknown  parameters  that are estimated from the  data. Nonparametric regression  refers to techniques that allow the regression function to lie in a specified set of  functions, which may beinfinite-dimensional. The performance of regression analysis methods in practice depends on the form of the data-generating process, and how it relates to the regression approach being used. Since the true form of the data-generating process is not known, regression analysis depends to some extent on making assumptions about this process. These assumptions are sometimes (but not always) testable if a large amount of data is available. Regression models for prediction are often useful even when the assumptions are moderately violated, although they may not perform optimally. However when carrying out  inference  using regression models, especially involving small  effects  or questions of  causality  based on  observational data, regression methods must be used cautiously as they can easily give misleading results. Underlying assumptions Classical assumptions for regression analysis include: ? The sample must be representative of the population for the inference prediction. ? The error is assumed to be a  random variable  with a mean of zero conditional on the explanatory variables. ? The variables are error-free. If this is not so, modeling may be done using  errors-in-variables model  techniques. ? The predictors must be  linearly independent, i. e. it must not be possible to express any predictor as a linear combination of the others. SeeMulticollinearity. The errors are  uncorrelated, that is, the  variance-covariance matrix  of the errors is  diagonal  and each non-zero element is the variance of the error. ? The variance of the error is constant across observations (homoscedasticity). If not,  weighted least squares  or other methods might be used. These are sufficient (but not all necessary) conditions for the least-squares estimator to possess desirable propertie s, in particular, these assumptions imply that the parameter estimates will be  unbiased,  consistent, and  efficient  in the class of linear unbiased estimators. Many of these assumptions may be relaxed in more advanced treatments. Basic Formula of Regression Analysis:- X=a+by (Regression line x on y) Y=a+bx (Regression line y on x) 1st – Regression equation of x on y:- 2nd – Regression equation of y on x:- Regression Coefficient:- Case 1st – when x on y means regression coefficient is ‘bxy’ Case 2nd – when y on x means regression coefficient is ‘byx’ Least Square Estimation:- The main object of constructing statistical relationship is to predict or explain the effects on one dependent variable resulting from changes in one or more explanatory variables. Under the least square criteria, the line of best fit is said to be that which minimizes the sum of the squared residuals between the points of the graph and the points of straight line. The least squares method is the most widely used procedure for developing estimates of the model parameters. The graph of the estimated regression equation for simple linear regression is a straight line approximation to the relationship between y and x. When regression equations obtained directly that is without taking deviation from actual or assumed mean then the two Normal equations are to be solved simultaneously as follows; For Regression Equation of x on y i. e. x=a+by The two Normal Equations are:- For Regression Equation of y on x i. e. y=a+bx The two Normal Equations are:- Remarks:- 1- It may be noted that both the regression coefficient ( x on y means bxy and y on x means byx ) cannot exceed 1. 2- Both the regression coefficient shall either be positive + or negative -. 3- Correlation coefficient (r) will have same sign as that of regression coefficient.

What the In-Crowd Wont Tell You About Which Pattern of Organization Presents Essay Topics in Order of Rising or D

What the In-Crowd Won't Tell You About Which Pattern of Organization Presents Essay Topics in Order of Rising or D Instead of continue to eliminate money required to run the bus system, the city altered the law. Secondly, surpluses that could feed many folks are often destroyed so as to keep the cost of merchandise high. The report describes quite a few reasons and events that caused the many wars and instances of violence that have broken out over recent years. On the flip side, in the nation, you're always among familiar faces. But in the nation, you always have the option to find peace and quiet. An effect is the thing that happens due to that function. For instance, the statement is often made that drug abuse is a health problem rather than a criminal justice issue. We all understand that starting instructions from the start and giving each in depth step in the order it should happen is essential to having an excellent outcome, within this event a yummy pie! In reality , the subject of war generally speaking has many causes with specific outcomes. The Pain of Which Pattern of Organization Presents Essay Topics in Order of Rising or D You're able to observe that this sort of organization is best when describing things that occur over time. In the city, you're constantly exposed to new and unique kinds of individuals. Though some students feel I am just being mean, there are lots of good reasons for this rule. Taking in different people's ideas will allow you to see new methods to approach your own writing and thinking. The truth is not as clear-cut. Putting a plan in place may also help save you time later as you'll have the ability to rearrange things even before you commence writing. The Ultimate Which Pattern of Organization Presents Essay Topics in Order of Rising or D Trick Another sensible pick is when Porter chose to incorporate an account of what a real friend is and the way that friend may move in a specific state of affairs. It' s essential to note that they ought to not be a starting point for writers who wish to write something authenticsomething they care deeply about. You may use it any time you're writing a persuasive piece, which usually means you're making an argument or attempting to convince your reader to believe or execute a particular action. Explain the reason why this is an issue, and mention who should be worried about it. Likewise, if a comparison is recommended, you would like to be aware the points that are alike in nature. Maybe you found the very best reason to recycle is it saves trees, which enables the environment. If You Read Nothing Else Today, Read This Report on Which Pattern of Organization Presents Essay Topics in Order of Rising or D As an example, imagine you're writing an essay on the significance of recycling. Here, it is possible to also find out more about other measures to writing a great research paper. Whatever you write, you are going to require a strong intro duction. This is sometimes thought of as a particular format or the way the writing is organized. Writing the background often offers you a notion of how you wish to do the intro, and therefore you don't need to fret over it. For instance, a biography is the story of an individual's life. To begin with, the body ought to be split into three or more paragraphs. The fundamental unit of thought possibly one of the greatest approaches to boost your reading ability is to learn how to read paragraphs effectively. Third, all body paragraphs ought to be logically connected by way of transitions. Anticipating the order where the material is going to be presented helps you place the facts into perspective and to observe the way the parts fit in the whole. This plan of action is the order where the material will be displayed in the text. Ruthless Which Pattern of Organization Presents Essay Topics in Order of Rising or D Strategies Exploited Let's take a good look at those forms o f organizational patterns. Let's look at a good example of a topic that suits well with this pattern. The Ugly Secret of Which Pattern of Organization Presents Essay Topics in Order of Rising or D As soon as your paper is full of bits of information, you may use a very simple numbering system to get started identifying topics and subtopics. The option of organizational pattern is contingent on the information and the writer's purpose. We are happy to present you a common organization of a research paper at this time. You've probably researched it and collected necessary info. You're almost ready to begin writing, but you aren't certain how to organize all information and ideas you've got. Within this very first stage of information gathering, you ought not be concerned about organizing your information. Your intention is to anticipate the total pattern and set the facts into a wide perspective. You'll choose one over the other dependent on the type of tone you want to cr eate and the way you want to affect your audience. So, among the first things that you should do when attempting to understand a challenging text is to work out the specific organization pattern. You are going to understand that the thoughts result in a general impression (in italics). Ponder the information for a couple moments and see whether it's possible to boil it all down to a thought. The Argument About Which Pattern of Organization Presents Essay Topics in Order of Rising or D In either instance, you can look to these common techniques of development to figure out ways to sharpen those vague topics or to add support where required. We must mention an introduction has an important part in the total research paper organization. Maybe they lack a very clear subject, or perhaps they lack support. For persuasive writing, you can state the issue and then all of the probable solutions.

The Realist Perspective of the Cuban Missile Crisis

The Cuban Missile Crisis lasted two weeks in the midst of the Cold War, and brought the world closer to nuclear war than ever before. In October of 1962 multiple nuclear missiles of the Soviet Union’ s were discovered in Cuba, a mere 90 miles south of the United States. Given the communist ties between Cuba and the USSR, this poised a considerable threat to our national security. Throughout the 14 days the two leaders, John F. Kennedy and Nikita Khrushchev struggled to clearly understand each others‘ genuine intentions. Actions taken by each state during this crisis demonstrates the realist point of view, in a variety of ways. The fundamentals of Realism will be explored and explained along with actions taken during this crisis from a†¦show more content†¦The Moscow Kremlin declared Soviet would support Cuba in February of 1962, and by July secret agreements on economic and military cooperation were signed. Almost immediately the Soviet Union sent various milita ry equipment including, heavy bombers, rocket launchers, tanks, helicopter, and nuclear submarines. (CITE) Over the summer construction of several missile sites began, once discovered President Kennedy issued a stern warning to Cuba. According to realism, a state should seek arms, increase their military strength, and make alliances with those who can protect them from potential threats (Charles and Raymond 28). On October 14th an American U-2 aircraft took pictures of nuclear missiles under construction in Cuba, and this was the beginning of the Cuban Missile Crisis. The USSR made the decision to put Soviet missiles in Cuba, to create a â€Å"balance of power†. The Soviet Union considered the US missiles placed in Turkey as a threat and needed a way to counterbalance this to secure their safety. The main motivation for this action was to create a balance of power between the two. Realism believes each state is entirely responsible for its own security and survival, and expec ts a balance of power. On October 22nd, another U-2 flight revealed missile sites being rapidly assembled immediately Kennedy ordered a naval quarantine of Cuba. That night he wrote a letter to KhrushchevShow MoreRelatedThe Cuban Missile Crisis And The Soviet Union1412 Words   |  6 PagesThe Cuban Missile Crisis became the closest the world had ever been to nuclear war, resulting from growing tension in the Cold War between the United States (NATO) and the Soviet Union (Warsaw Pact). Cuba at the time also had ongoing conflict with the United States, after the failed Bay of Pigs Invasion in attempt to overthrow corrupt government leader Fidel Castro. 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This makes the crisis one of the most essential events in international affairs history, demonstrating a great example of the realist perspectives and other important aspects of international relations. Primarily, the origins of the Cuban Missile Crisis can be readily attributed to the realist perspective. In 1961, President John F. Kennedy launched the Bay of Pigs Invasion of Cuba, which was a thwartedRead MoreJfk And Khrushchev s Impact On The World War II1293 Words   |  6 Pagespeople would remember as the closest we ever came to a nuclear war. To many Americans this was very frightening; we have all heard what nuclear weapons can do. No one wants to feel the effects of these nuclear weapons. But you may ask, what caused the crisis and why did it not end in World War III? Who and/or what were the most important actors, structures and institutions involved? And most importantly, which characteristics of those actors, structures and institutions provide the strongest, clearestRead MoreThe Issue Of Nuclear Weapons883 Words   |  4 PagesRussia, and China – no major nuclear power has gotten into a nuclear war with another major nuclear power. Nor have they engaged in a direct conflict involving conventional weapons. They have come close, as seen in the Cuban Missile Crisis, but they have not traded nuclear missiles or bombs with each other. The only two states that have been in conflict with each other and have nuclear weapons stockpiles are India and Pakistan in the Indo-Pakistani War of 1999, which was small in scale and quicklyRead MoreThe United States And The Cold War Essay1614 Words   |  7 Pagesthe First World War. In general, a cold war is a state of perpetual conflict where there is no direct milit ary intervention, but actions are taken strategically, politically and economically (plus sabotage and other indirect denotes); From this perspective there have been historically different cold wars, but in verbalizing of this I’m referring to the conflict that I will relate in this essay. After World War II, the United States and the Soviet Union were the world’s most vigorous nations. TheyRead MoreWar Is An Inevitable Feature Of International Politics1560 Words   |  7 PagesUnited Nations. Can such security organisations including, non-governmental organizations really prevent conflicts? We have seen the inevitability of wars through the history, from which has arisen decades of theoretical debates (First ideologist-realist great debate took place between 1930’s and 1940’s, which focus was on the Nazi threat as well). Why is security crucial? Is there any alternative solution to abolish armed conflicts and struggles between states; or can we concl ude, that war is inevitableRead MoreForeign Policies Big And Small Affect Our Lives1413 Words   |  6 Pagesisn’t enough to determine what their agendas and perspectives may be. The two most influential general perspectives of foreign policy are the realist and liberal perspectives. Kaufman describes realism on pages 10-11 as a assumption that â€Å"†¦nation-states are the primary actors in world politics and that each will act in a way that allows it to pursue its key interests or ‘national interests.’† He contrasts that viewpoint with the liberal perspective that â€Å"looks at countries as a part of a collectiveRead MoreGeneral Curtis Lemay : An Effective Leader And Problem Solver1647 Words   |  7 Pagesmore bombs on target with fewer losses than other groups. After his successful bombing raids over France and Germany, he tested his methods again in other theater of war. LeMay’s toughts on the protracted and bloody war against Japan were purely realists â€Å"It was a long drawn out war. You began to get casualties from the side effects-the exhaustion, deprivation, disease and things of that sort. So getting it over with as quickly as possible is the moral responsibility of everyone concerned.† MoreoverRead MoreUnited States Grand Strategy during the Cold War with Emphasis on the Conflict in Vietnam2740 Words   |  11 PagesIntroduction - Analysis of U.S. grand strategy during the Vietnam War cannot be fully understood without placing it in the context of the Cold War and the foreign policy of â€Å"containment.† In this context, details indicate that realist, liberalist, and constructivist theories all contributed to U.S. grand strategy at the time. However, more detailed analysis reveals that, while defensive realism was guiding foreign policy during this period of the cold war, offensive realism was the predominant